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Streamline JIT profiling

Hi, I'm trying to measure the power of a deep learning model at Raspberry Pi, Jetson, etc ..

And I have just three questions.

1. The description page of v 6.x contains information about Python code profiling, but it was not on the description page of v 7.x.

Did the function get deleted after moving on to version 7?

2. Is code profiling function available even if I use NIDAQ equipment instead of Energy Probe?

 

3. The figure on the description page showed NI USB-621x as an example, is that the only line available? If so, which device is appropriate?(e.g. USB-6211)

(Arm Streamline User Guide Version 7.5)

Parents
  • Thanks a lot!

    I am trying to load a deep learning model on Raspberry Pi, infer one data, and obtain records such as power in the meantime. The language used is Python, and I want to obtain measurement records only where the model runs(predicts) in the structure as shown below.

    ...

    model = tf.keras.models.load_model('model')

    y = model.predict(data_x)   # Here is where I want to log

    ...

    The size of the model can be very small, so the inference time may be about 1 ms. Then is it okay to use the python profiler function of 6.x version?

    If not, how can I log that part?

    Thanks

Reply
  • Thanks a lot!

    I am trying to load a deep learning model on Raspberry Pi, infer one data, and obtain records such as power in the meantime. The language used is Python, and I want to obtain measurement records only where the model runs(predicts) in the structure as shown below.

    ...

    model = tf.keras.models.load_model('model')

    y = model.predict(data_x)   # Here is where I want to log

    ...

    The size of the model can be very small, so the inference time may be about 1 ms. Then is it okay to use the python profiler function of 6.x version?

    If not, how can I log that part?

    Thanks

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